PARENT SESSION
Oral Session #29: Spatial Ecology and Disturbance Ecology.
Presiding: J. Ludwig
Tuesday, August 6. 8:00 AM to 11:30 AM. Coconino Meeting Room, TCC.
Mapping foliar nitrogen concentration for spatially explicit parameterization of PnET-II ecosystem model for the Southern US .
Mao, Zhiyan*,1, Sun, Ge1, McNulty, Steve2, Gavazzi, Mike2, 1 North Carolina State University, Raleigh, NC2 US Forest Service, Raleigh, NC
ABSTRACT- Parameterization is one of the main factors limiting the accuracy and credibility of large-scale model simulations, and spatially explicit key parameters would help reduce the simulation uncertainty compared with generalized parameters. Foliar nitrogen concentration is a key parameter of PnET-II ecosystem model. Two statistical approaches will be employed and contrasted in this study to quantify the spatial patterns of foliar nitrogen concentration variability across the Southern US region: classification and regression tree (CART) analysis and logistic regression techniques. For both approaches, site level data based on literature search and field study were collected including the following variables: foliar nitrogen concentration of individual species (or dominant species of forest), forest type, foliar life span, latitude, elevation, temperatures (mean January, mean July and mean annual), annual precipitation, annual actual evapotranspiration, and mean monthly solar radiation in foliar life time. Climate data were retrieved from either local weather stations or existing nation-wide climate data sets (4 kilometer resolution). Geostatistical approaches such as kriging were used for interpolation of some variables with missed values. Within a Geographic Information System integrating all the variables from over 120 sites distributed in the 13 states of the Southern US region, logistic regression model and CART model will be used separately to explore the variation of foliar nitrogen concentration in relation to those climatic, geographic and genotypic constrains. The modeling results will then be extrapolated to the entire region for estimating and mapping the foliar nitrogen concentration of each 4 km grid cell of the region based on the correlations. Further study will be conducted to quantify and reduce the uncertainties introduced by data accuracy and model structure.
KEY WORDS: foliar nitrogen concentration, pnet model, regression tree model, geographical information system